Flexible and robust modelling of volatility comovements: a comparison of two multifractal models

Arbeitspapier

Long memory (long-term dependence) of volatility counts as one of the ubiquitous stylized facts of financial data. Inspired by the long memory property, multifractal processes have recently been introduced as a new tool for modeling financial time series. In this paper, we propose a parsimonious version of a bivariate multifractal model and estimate its parameters via both maximum likelihood and simulation based inference approaches. In order to explore its practical performance, we apply the model for computing value-at-risk and expected shortfall statistics for various portfolios and compare the results with those from an alternative bivariate multifractal model proposed by Calvet et al. (2006) and the bivariate CC-GARCH of Bollerslev (1990). As it turns out, the multifractal models provide much more reliable results than CC-GARCH, and our new model compares well with the one of Calvet et al. although it has an even smaller number of parameters.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Kiel Working Paper ; No. 1594

Classification and Topics

• Classification: Wirtschaft ; Bayesian Analysis: General ; Estimation: General ; International Financial Markets
• Subject: Long memory ; multifractal models ; simulation based inference ; value-at-risk ; expected shortfall

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Liu, Ruipeng ; Lux, Thomas
• Event: Veröffentlichung
• (who): Kiel Institute for the World Economy (IfW)
• (where): Kiel
• (when): 2010

Further information

• Handle: http://hdl.handle.net/10419/30048
• Last update: 10.03.2025, 11:42 AM CET